1 / 33

Data Collection and Analysis for Students with Autism

Data Collection and Analysis for Students with Autism. Meredith Eads, M.Ed. Dr. Judy Marco October 28, 2008. Why Collect Data?. Data will help you: Identify patterns Make data-driven decisions Modify your delivery of instruction Feel more confident Enlist support

madra
Download Presentation

Data Collection and Analysis for Students with Autism

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Data Collection and Analysis for Students with Autism Meredith Eads, M.Ed. Dr. Judy Marco October 28, 2008

  2. Why Collect Data? Data will help you: • Identify patterns • Make data-driven decisions • Modify your delivery of instruction • Feel more confident • Enlist support • Communicate & Provide information • Stand by your classroom decisions

  3. Why collect data? • Meet suggested skill competencies developed by Virginia Autism Council • Avoid lawsuits, or defend yourself in case they do happen • IDEIA (2004) requires a student’s individualized education plan (IEP) to include: A statement of how the child’s progress toward the annual goals will be measured. • In a nutshell…because we have to.

  4. What constitutes data? Data is defined as: factual information (as measurements or statistics) used as a basis for reasoning, discussion, or calculation.

  5. What constitutes data? Rank ordered most to least effective • Data Sheets and associated graphs • Behavior Sheets • Mainstream checklists • DRA • Benchmark Tests • Formal Observations • Anecdotal Records • Grades • Student work These are more subjective, therefore are less accurate, and cannot be used as sole source of information

  6. Data Collection Examples Curriculum-based Assessments Recording observations

  7. Data Collection:Curriculum-based Assessment (CBA) Repeated measures of a student’s progress within the classroom curriculum Results analyzed to see if learning environment or instructional techniques are working for the student Results help teachers redesign instruction

  8. Data Collection Tool Example Example: Given 2-4 syllable words, Eddie will identify, by clapping, the number of syllables in words presented orally with 90% accuracy on 3 consecutive probes.

  9. Data Collection:Observation & Recording This type of data collection is individualized to address specific IEP academic and behavioral goals. Is not linked to set curriculum or standardized assessment.

  10. Identify a Behavior to Measure What challenging behavior is interfering most with the student’s learning or the learning of others? What positive behaviors are you trying to increase? Make sure it is observable and quantifiable.

  11. Guidelines for Behavior Selection • Functional • Age-appropriate • Realistic • Goal behavior or prerequisite behavior • Socially valid • Likely to generalize and be maintained in the natural environment

  12. Observable Which can you see/measure? • Is noncompliant • Completes assignments • Responds to greetings • Throws toys • Is lazy and unmotivated • Is nice to peers

  13. Operational Definitions Define the behaviors so that they pass the “stranger test” – what, exactly do they look like? Provide clear parameters, as well as non-examples. Example: “Self-Injurious Hitting” = The student hits himself on the head with an open hand. Each instance is separated by the hand lifting off of the head. Does not include closed-fisted punches to own head, or any kind of hits to others.

  14. Some Behaviors to Operationalize: • Matching objects • Multiplying • Spelling • Using appropriate classroom behavior

  15. What should I record? • Frequency • Number • Duration • Latency • Proportion/percent • Interval • Quality • Intensity • * Difficult for these above to be objective, so develop or find standards around them.

  16. Rubric for Rating the Intensity of Disruptive Behavior

  17. When do you collect data? Whenever you need to assess: • performance on IEP goals • academic mastery • task mastery • behavior

  18. How often do you need to collect data? Often enough to notice trends and make data-driven decisions in the classroom

  19. Where can you collect data? Anywhere and Everywhere

  20. Who gathers data? • Anyone who works with the student • The instructional assistant • The student • The teacher

  21. Getting Started Make your data collection system useful. Make your data collection system relevant to the behavior being measured. Make data collection as painless as possible.

  22. Create what works for you!! • Keep it simple. • Keep it in easy access. • Take enough data to give you a clear picture of the student. • Rework and revise as necessary. • Beg, borrow, make it your own.

  23. IEP’s, Data, and Progress4 Steps

  24. Evaluation of Data:Decision Rules Decision rules are used to help guide the teacher as he/she evaluates a student’s data The data points may indicate that the teacher should Inquire about changes in external variables Wait Make instructional adjustment Raise the goal

  25. Making Instructional Adjustments Classroom climate Time of day Motivation What is taught Skill focus Amount of practice How it is taught Materials Group size Prompting and other supports

  26. Communicating the Data Appropriate representation should be Simple Stand alone Understandable

  27. Reviewing the Data Talk about: • Trends in the data; what is the general direction of change? • Progress toward socially significant difference • Steps toward independence, inclusion, access to general curriculum, communication • Modifications that have been made to adjust teaching

  28. Dear Eddie’s Parents, Look how well Eddie has done on his IEP goal. He has met his target of 18 correct for the last four weeks. Let’s schedule an IEP meeting to talk about where we should go from here. Sincerely,Eddie’s Teacher Communication Example

  29. Legal Decisions: Can you stand by your data? • Absence of adequate progress monitoring has been the focus of several administrative and judicial decisions • Courts unwilling to accept claims of school districts appropriateness of a student’s program without proof in the form of data. Etscheidt, Susan K. (2006)

  30. Legal Decisions • Recent decisions concerning progress monitoring reveal five areas of concern (Etscheidt, S. K. , 2006): • IEP team fails to develop or implement progress monitoring plans; • Responsibilities for progress monitoring are improperly delegated;

  31. IEP team does not plan or implement progress monitoring for behavior intervention plans (BIPs); • The team uses inappropriate measures to determine student progress toward graduation;

  32. Progress monitoring is not frequent enough to meet the requirements of IDEIA or to provide meaningful data to IEP teams.

  33. References Etscheidt, Susan K. (2006). Progress monitoring: Legal issues and recommendations for IEP teams. TEACHING Exceptional Children, 56-60. Cited within - The IEP Progress Monitoring Process www.swoserrc.org/uploads/IEPDevelopment-ProgressMonitoringPart3.pps http://www.polyxo.com/data/

More Related